{"id":"W1596225789","doi":"10.1109/icassp.1986.1168698","title":"Proper orthogonal projection - multiple signal classification (POP-MUSIC)","year":2005,"lang":"en","type":"article","venue":"","topic":"Image and Signal Denoising Methods","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Multiple signal classification; SIGNAL (programming language); Orthographic projection; Computer science; Projection (relational algebra); Spectral density estimation; Linear prediction; Spurious relationship; Maximum likelihood; Algorithm; Mathematics; Estimation theory; Speech recognition; Artificial intelligence; Statistics; Telecommunications; Fourier transform","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000857024,0.001221515,0.001038379,0.001063281,0.0005905514,0.001721764,0.001153368,0.001183865,0.003504386],"category_scores_gemma":[0.003089204,0.0004945603,0.0006599133,0.001948418,0.001335769,0.00186622,0.001395589,0.001355948,0.002452912],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003520382,"about_ca_system_score_gemma":0.0008429161,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004595006,"about_ca_topic_score_gemma":0.0006678709,"domain_scores_codex":[0.9988305,0.0002630461,0.00007973933,0.0001786101,0.0005680105,0.00008011175],"domain_scores_gemma":[0.9990783,0.0002663055,0.0001163936,0.0002117787,0.000291256,0.0000360114],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001993959,0.00006709341,0.0009972375,0.0004878283,0.0000870115,0.0005758496,0.0001738494,0.03870269,0.04430037,0.2161353,0.01112043,0.6871529],"study_design_scores_gemma":[0.0000331212,0.000374452,0.0008954,0.0001158666,0.00006079836,0.002593715,0.0001018037,0.8014067,0.05305713,0.0766521,0.06458824,0.0001207069],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00100505,0.0004298023,0.9962246,0.00007707761,0.0001450964,0.00002875646,0.00003036013,0.0003606092,0.00169854],"genre_scores_gemma":[0.0449271,0.001532517,0.9491714,0.0001674541,0.000311002,0.0001216667,0.0002326154,0.0001489299,0.003387274],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003504386,"threshold_uncertainty_score":0.0117234,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06445578515363094,"score_gpt":0.2861018745690428,"score_spread":0.2216460894154119,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}